Recently I tried to use the "GAN Theft Auto" sample dataset from YouTuber Sentdex to make my own simulated GTA stretch of road.
Here is his GitHub repository: GANTheftAuto and his original video: video

Of course, instead of using Nvidia's "GameGAN" framework, I use AOgmaNeo!

Using AOgmaNeo for this task has one huge advantage - it runs much, much faster. Sentdex trained on an Nvidia DGX A100 workstation, which is currently one of the most powerful workstations Nvidia makes. With AOgmaNeo however, one only needs a regular desktop CPU.

Here is a link to my results (using AOgmaNeo).

It's not as detailed as that of Sentdex, since I only have the sample dataset and I am also not using upscaling. However, I am surprised it works this well given the vast difference in compute needed.

The code for training uses the Python bindings to AOgmaNeo (PyAOgmaNeo), and is available here.